Intention recognition

ABSTRACT

Some embodiments provide an autonomous navigation system which autonomously navigates a vehicle through an environment based on predicted trajectories of one or more separate dynamic elements through the environment. The system identifies contextual cues associated with a monitored dynamic element, based on features of the dynamic element and actions of the dynamic element relative to various elements of the environment, including motions relative to other dynamic elements. A monitored dynamic element can be associated with a particular intention, which specifies a prediction of dynamic element movement through the environment, based on a correlation between identified contextual cues associated with the monitored dynamic element and a set of contextual cues which are associated with the particular intention. A predicted trajectory of the dynamic element is generated based on an associated intention. A targeted signal can be directed to a target dynamic element based on a predicted trajectory of the dynamic element.

This application is a 371 of PCT Application No. PCT/US2016/050621,filed Sep. 8, 2016, which claims benefit of priority to U.S. ProvisionalPatent Application No. 62/215,672, filed Sep. 8, 2015. The aboveapplications are incorporated herein by reference. To the extent thatany material in the incorporated application conflicts with materialexpressly set forth herein, the material expressly set forth hereincontrols.

BACKGROUND Technical Field

This disclosure relates generally to autonomous navigation of a vehicle,and in particular to an autonomous navigation system which can beincluded in a vehicle and which navigates the vehicle in an environment,which includes various dynamic elements, based on predictingtrajectories of the dynamic elements based on recognizing contextualcues associated with the elements and the environment.

Description of the Related Art

The rise of interest in autonomous navigation of vehicles, includingautomobiles, has resulted in a desire to develop autonomous navigationsystems which can autonomously navigate (i.e., autonomously “drive”) avehicle through various routes, including one or more roads in a roadnetwork, such as contemporary roads, streets, highways, etc.

In some cases, autonomous navigation is enabled via an autonomousnavigation system (ANS) which can process and respond to detection ofvarious elements in an external environment, including static features(e.g., roadway lanes, road signs, etc.) and dynamic features (presentlocations of other vehicles in a roadway on which the route extends,present locations of pedestrians, present environmental conditions,roadway obstructions, etc.) along a route in real-time as they areencountered, thereby replicating the real-time processing and drivingcapabilities of a human being.

In some cases, autonomous navigation includes navigating a vehicle inresponse to detection of one or more traffic participants in theenvironment through which the vehicle is being navigated. For example,where another vehicle is detected ahead of the navigated vehicle and isdetermined to be moving slower than the navigated vehicle, such that thenavigated vehicle is approaching the other vehicle, the navigatedvehicle can be slowed or stopped to prevent the vehicle pathsintersecting. In another example, where a pedestrian is identified nearan edge of the roadway along which the vehicle is being navigated, thevehicle can be slowed or stopped in response to detection of thepedestrian.

SUMMARY OF EMBODIMENTS

Some embodiments provide an autonomous navigation system whichautonomously navigates a vehicle through an environment based onpredicted trajectories of one or more separate dynamic elements throughthe environment. The system identifies contextual cues associated with amonitored dynamic element, based on features of the dynamic element andactions of the dynamic element relative to various elements of theenvironment, including motions relative to other dynamic elements. Amonitored dynamic element can be associated with a particular intention,which specifies a prediction of dynamic element movement through theenvironment, based on a correlation between identified contextual cuesassociated with the monitored dynamic element and a set of contextualcues which are associated with the particular intention. A predictedtrajectory of the dynamic element is generated based on an associatedintention. A targeted signal can be directed to a target dynamic elementbased on a predicted trajectory of the dynamic element.

Some embodiments provide an apparatus which includes an autonomousnavigation system which can be installed in a vehicle and canautonomously navigate the vehicle through an environment in which thevehicle is located. The autonomous navigation system is configured toidentify a set of contextual cues associated with a dynamic elementlocated in the environment, wherein each contextual cue indicates one ormore particular features associated with the dynamic element, based onmonitoring at least a portion of the environment; associate the dynamicelement with a particular set of predicted motions, based on adetermination of a correlation between the identified set of contextualcues and a predetermined set of contextual cues which are associatedwith the particular set of predicted motions; generate a predictedtrajectory of the dynamic element through the environment based on theparticular set of predicted motions associated with the dynamic element;and generate a set of control commands which, when executed by one ormore control elements installed in the vehicle, cause the vehicle to benavigated along a driving route which avoids intersection with thepredicted trajectory of the dynamic element.

Some embodiments provide a method which includes identifying a set ofcontextual cues associated with a dynamic element located in theenvironment, wherein each contextual cue indicates one or moreparticular features associated with the dynamic element, based onmonitoring at least a portion of the environment; associating thedynamic element with a particular set of predicted motions, based on adetermination of a correlation between the identified set of contextualcues and a predetermined set of contextual cues which are associatedwith the particular set of predicted motions; generating a predictedtrajectory of the dynamic element through the environment based on theparticular set of predicted motions associated with the dynamic element;and generating a set of control commands which, when executed by one ormore control elements installed in the vehicle, cause the vehicle to benavigated along a driving route which avoids intersection with thepredicted trajectory of the dynamic element.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a schematic block diagram of a vehicle whichcomprises an autonomous navigation system (ANS), according to someembodiments.

FIG. 2 illustrates an overhead view of an environment in which multipledynamic elements are located, including a vehicle which is autonomouslynavigated through the environment and includes a set of sensors whichcan generate sensor data associated with the dynamic elements and anautonomous navigation system which can determine a particular predictedtrajectory of a dynamic element based on contextual cues identified inthe sensor data, according to some embodiments.

FIG. 3 illustrates an overhead view of an environment in which multipledynamic elements are located, including a vehicle which is autonomouslynavigated through the environment and includes a set of sensors whichcan generate sensor data associated with the dynamic elements and anautonomous navigation system which can determine a particular predictedtrajectory of a dynamic element based on contextual cues identified inthe sensor data, according to some embodiments.

FIG. 4 illustrates an overhead view of an environment in which multipledynamic elements are located, including a vehicle which is autonomouslynavigated through the environment and includes a set of sensors whichcan generate sensor data associated with the dynamic elements and anautonomous navigation system which can determine a particular predictedtrajectory of a dynamic element based on contextual cues identified inthe sensor data, according to some embodiments.

FIG. 5 illustrates generating an intention association betweenidentified contextual cues and subsequent predicted dynamic elementmovements, according to some embodiments.

FIG. 6 illustrates autonomously navigating a vehicle through an externalenvironment based on a predicted trajectory of a dynamic element in theexternal environment, according to some embodiments.

FIG. 7 illustrates an overhead view of an environment in which multipledynamic elements are located, including a vehicle which is autonomouslynavigated through the environment and includes a set of indicators whichcan generate a set of targeted signals which are transmitted to specificdynamic elements in the external environment, according to someembodiments.

FIG. 8 illustrates generating targeted signals which are directed toparticular target dynamic elements, according to some embodiments.

FIG. 9 illustrates an example computer system configured to implementaspects of a system and method for autonomous navigation, according tosome embodiments.

This specification includes references to “one embodiment” or “anembodiment.” The appearances of the phrases “in one embodiment” or “inan embodiment” do not necessarily refer to the same embodiment.Particular features, structures, or characteristics may be combined inany suitable manner consistent with this disclosure.

“Comprising.” This term is open-ended. As used in the appended claims,this term does not foreclose additional structure or steps. Consider aclaim that recites: “An apparatus comprising one or more processor units. . . .” Such a claim does not foreclose the apparatus from includingadditional components (e.g., a network interface unit, graphicscircuitry, etc.).

“Configured To.” Various units, circuits, or other components may bedescribed or claimed as “configured to” perform a task or tasks. In suchcontexts, “configured to” is used to connote structure by indicatingthat the units/circuits/components include structure (e.g., circuitry)that performs those task or tasks during operation. As such, theunit/circuit/component can be said to be configured to perform the taskeven when the specified unit/circuit/component is not currentlyoperational (e.g., is not on). The units/circuits/components used withthe “configured to” language include hardware—for example, circuits,memory storing program instructions executable to implement theoperation, etc. Reciting that a unit/circuit/component is “configuredto” perform one or more tasks is expressly intended not to invoke 35U.S.C. § 112, sixth paragraph, for that unit/circuit/component.Additionally, “configured to” can include generic structure (e.g.,generic circuitry) that is manipulated by software and/or firmware(e.g., an FPGA or a general-purpose processor executing software) tooperate in manner that is capable of performing the task(s) at issue.“Configure to” may also include adapting a manufacturing process (e.g.,a semiconductor fabrication facility) to fabricate devices (e.g.,integrated circuits) that are adapted to implement or perform one ormore tasks.

“First,” “Second,” etc. As used herein, these terms are used as labelsfor nouns that they precede, and do not imply any type of ordering(e.g., spatial, temporal, logical, etc.). For example, a buffer circuitmay be described herein as performing write operations for “first” and“second” values. The terms “first” and “second” do not necessarily implythat the first value must be written before the second value.

“Based On.” As used herein, this term is used to describe one or morefactors that affect a determination. This term does not forecloseadditional factors that may affect a determination. That is, adetermination may be solely based on those factors or based, at least inpart, on those factors. Consider the phrase “determine A based on B.”While in this case, B is a factor that affects the determination of A,such a phrase does not foreclose the determination of A from also beingbased on C. In other instances, A may be determined based solely on B.

DETAILED DESCRIPTION

Some embodiments include one or more vehicles in which an autonomousnavigation system (“ANS”) is included, where the ANS identifies dynamicelements in a common external environment in which the one or morevehicles are located, predicts a trajectory of certain dynamic elementsbased on contextual cues associated with one or more of the dynamicelements, and autonomously navigates the vehicle based on the predictedtrajectories of the dynamic elements along a driving route which avoidsintersections with the trajectories of the dynamic elements.Autonomously navigating a vehicle along a driving route which avoidsintersections with the trajectories of one or more of the dynamicelements includes navigating the vehicle along a driving route whichavoids paths intersecting between the one or more vehicles and the oneor more dynamic elements.

In some embodiments, the ANS autonomously navigates the vehicle along adriving route via generation of control commands associated with variouscontrol elements of the vehicle, where the control commands, whenreceived at the associated control elements, cause the control elementsto navigate the vehicle along the driving route.

In some embodiments, the ANS generates a driving route through anexternal environment based at least in part upon various static elementsand dynamic elements included in the external environment. Staticelements can include roadway features, including roadway lanes, curbs,etc., traffic signs and traffic signals, flora, artificial structures,inanimate objects, etc. Dynamic elements can include a time of day,local weather conditions, fauna, traffic participants, etc. in theexternal environment. Traffic participants can include vehicles,pedestrians, some combination thereof, etc. located in the externalenvironment, including traffic participants located proximate to or inthe roadway along which the vehicle is located.

The ANS, in some embodiments, generates a driving route based on variousdetected static elements and dynamic elements in the externalenvironment, where the driving route includes a route, via which thevehicle can be navigated through the external environment, which avoidsintersection of the vehicle with one or more static elements, dynamicelements, etc. located in the external environment. For example, adriving route through an external environment can include a route whichavoids intersection with a static obstacle in the roadway along whichthe vehicle is being navigated, a traffic participant which includesanother vehicle navigating along the roadway in an opposite direction oftravel relative to the vehicle, etc.

In some embodiments, the ANS, to generate a driving route which avoidsintersection of the vehicle with various dynamic elements in an externalenvironment, generates predicted trajectories of one or more dynamicelements, including traffic participants, through at least a portion ofthe external environment. The ANS can generate, for a given dynamicelement, including a pedestrian, a predicted trajectory of the dynamicelement through the external environment for a particular future amountof elapsed time. A predicted trajectory can include a predictedposition, velocity, acceleration, etc. of the dynamic element throughthe external environment at one or more future points in time. As aresult, based on the predicted trajectory of the dynamic element, theANS can predict a future position, velocity, acceleration, etc. of thedynamic element in the external environment at various future points intime. The ANS can generate a driving route along which the ANS cannavigate a vehicle, where the driving route avoids intersection with thedynamic element at any of the future points in time, based on thepredicted trajectory of the dynamic element.

In some embodiments, the ANS generates a predicted trajectory of adynamic element through an external environment based on identifyingvarious contextual cues associated with the dynamic element and furtheridentifying an association between the identified contextual cues and aparticular dynamic element intention which can be associated with thedynamic element. The various contextual cues can be identified based onprocessing sensor data, generated by various sensor devices, whichincludes information associated with various portions of the externalenvironment, dynamic elements, static elements, etc. The association caninclude a predetermined association between a set of contextual cues andone or more particular dynamic element intentions, and identifying theassociation can be based on determining a correlation between theidentified contextual cues and at least some of the contextual cuesincluded in the association. Based on the correlation, the ANS canidentify the one or more dynamic element intentions included in theassociation and can associate the identified intention with the one ormore dynamic elements with which the correlated cues are associated. Anintention specifies one or more predicted future motions of anassociated dynamic element. The ANS can generate a particular predictedtrajectory of the dynamic element based at least in part upon theassociated intention.

In some embodiments, an ANS generates an association between a dynamicelement intention and a set of contextual cues based on monitoringmotions of a dynamic element in an external environment, which caninclude identifying various contextual cues associated with the dynamicelement, tracking movement of the dynamic element through theenvironment, generating an intention which specifies the trackedmovement of the dynamic element, and generating an association betweenthe generated intention and a set of identified contextual cuesassociated with the dynamic element.

The ANS can revise, refine, change, etc. an association over time basedon subsequent monitoring of one or more dynamic elements in one or moreexternal environments. In some embodiments, the ANS associates aconfidence value with a particular association and selectively enablesthe association to be used, in predicting dynamic element trajectoriesand generating driving routes, based on a determination that theconfidence value associated with the association exceeds a predeterminedthreshold value. The confidence value can be adjusted based on repeatedverifications that a dynamic element's actual movements through anenvironment at least partially correlates to the movements predicted byan intention which is associated with identified contextual cuesassociated with the dynamic element.

Autonomously navigating a vehicle through an environment based ondynamic element trajectories which are predicted based on contextualcues and associations between the contextual cues and the predictedtrajectories can provide augmented navigation relative to autonomousnavigation systems which predict future trajectories of dynamic elementsbased on tracked prior and present movement of the dynamic elementsthrough the environment. For example, where a dynamic element whichincludes a pedestrian is observed, via sensor data generated by avehicle sensor device, to approach a crosswalk across a roadway ahead ofthe vehicle at a particular rate of speed, the ANS can determine, basedon various contextual cues identified from at least the sensor data,that the predicted trajectory of the pedestrian which is associated withthe cues includes a trajectory which includes the pedestrian stopping atthe edge of the crosswalk rather than continuing through the crosswalkat the observed particular rate of speed. As a result, the ANS cangenerate a driving route which causes the vehicle to be navigatedthrough the crosswalk without decelerating, thereby providing augmentednavigation control relative to a system which predicts the futuretrajectory of the pedestrian based on the pedestrian's movement towardsthe crosswalk, as such a system may predict that the pedestrian wouldcontinue into the roadway, through the crosswalk, without stopping andmay thus command the vehicle to stop. Because the ANS predicts dynamicelement trajectories based on contextual cues and associated intentions,rather than extrapolating present motion into future motion, the ANS canprovide improved prediction of complex dynamic element trajectories andimproved safety and navigation of the vehicle, based on navigating thevehicle based on the improved prediction of dynamic element motionthrough the external environment.

In some embodiments, the ANS generates one or more targeted signalswhich are transmitted through the external environment to one or moretargeted elements in the external environment. The one or more targetedsignals can include information, also referred to herein as “content”,“signal content”, etc., which is included in the targeted signal basedon the element to which the targeted signal is transmitted. A targetedsignal can include a signal which is directed to a particular “target”dynamic element in the environment and comprises a signal axis and anglewhich is focused on the target dynamic element so that the recipients ofthe targeted signal are at least partially restricted to the targetdynamic element. In addition, in some embodiments, the targeted signalincludes content which is particularly associated with the targetdynamic element, relative to other dynamic elements in the environment.In some embodiments, the content is associated with a present state ofthe dynamic element, a predicted trajectory of the dynamic element, somecombination thereof, etc. In some embodiments, the content comprises amessage.

In some embodiments, the ANS generates the targeted signal directed at aparticular target dynamic element based on a determination that thetarget dynamic element lacks perception of the vehicle in which the ANSis included, where the targeted signal includes content which providesan indication, to the dynamic element, of the presence of the vehicle inthe environment. For example, where the dynamic element includes apedestrian which is determinate to be oriented in a direction whichresults in the vehicle being outside of the field of view of thepedestrian, the ANS can generate a targeted signal to the pedestrianwhich provides the pedestrian with an indication that the vehicle isproximate to the pedestrian. As a result, the targeted signal augmentsthe perception of the pedestrian, which can augment the safety of thevehicle and the pedestrian by mitigating a risk that the pedestrian willfollow a trajectory which intersects with the driving route along whichthe vehicle is being navigated. In addition, the ANS can predict, basedon the transmission of the targeted signal, that the pedestrian willfollow a trajectory based at least in part upon the content of thesignal, which can include following a trajectory which avoids thevehicle, and can further generate a driving route based on theprediction.

In some embodiments, the targeted signal includes a visual signal. Forexample, the targeted signal can be generated by one or more visualindicators, including one or more lights, included in the vehicle, wherea particular set of visual indicators are activated to generate aparticular visual signal. The visual indicators can include at least aportion of one or more headlight assemblies included in the vehicle,where a portion of the headlight assemblies can be adjusted to direct alight beam to a particular dynamic element in the environment. Theheadlight assemblies can be adjusted to provide a visual signal whichincludes a variable-intensity beam of light, including a series of lightbeam pulses, etc.

In some embodiments, a targeted signal includes an audio signal which isdirected at a particular dynamic element, including a trafficparticipant, instance of fauna, etc. located in the externalenvironment. The audio signal can be a directional signal which isfocused in angle and axis via various known systems and methods ofgenerating targeted audio signals, including one or more of beamforming,ultrasonic modulation, etc., so that the recipient of the audio signalis at least partially restricted to the target dynamic element to whichthe targeted signal is directed. As a result, the amplitude of thesignal can be reduced, relative to a non-targeted audio signal, whichcan result in reduced disturbances to other dynamic elements in theexternal environment as a result of the signal transmission. Inaddition, as a result of the amplitude of the targeted signal beingreduced relative to a non-targeted signal, information communicated tothe dynamic element via content in the targeted signal can be at leastpartially precluded from being received and interpreted by other dynamicelements in the environment, thereby providing at least some levelinformation security to the communication.

As referred to herein, a “driving route” includes a pathway along whicha vehicle is navigated. A driving route can extend from a startinglocation to another separate destination location, extend back to adestination location which is the same as the starting location, etc. Aroute can extend along one or more various portions of one or morevarious roadways. For example, a route between a home location and awork location can extend from a home driveway, through one or moreresidential streets, along one or more portions of one or more avenues,highways, toll ways, etc., and to one or more parking spaces in one ormore parking areas. Such routes can be routes which a user repeatedlynavigates over time, including multiple times in a given day (e.g.,routes between home and work locations may be travelled at least once ina given day).

Reference will now be made in detail to embodiments, examples of whichare illustrated in the accompanying drawings. In the following detaileddescription, numerous specific details are set forth in order to providea thorough understanding of the present disclosure. However, it will beapparent to one of ordinary skill in the art that some embodiments maybe practiced without these specific details. In other instances,well-known methods, procedures, components, circuits, and networks havenot been described in detail so as not to unnecessarily obscure aspectsof the embodiments.

It will also be understood that, although the terms first, second, etc.may be used herein to describe various elements, these elements shouldnot be limited by these terms. These terms are only used to distinguishone element from another. For example, a first contact could be termed asecond contact, and, similarly, a second contact could be termed a firstcontact, without departing from the intended scope. The first contactand the second contact are both contacts, but they are not the samecontact.

The terminology used in the description herein is for the purpose ofdescribing particular embodiments only and is not intended to belimiting. As used in the description and the appended claims, thesingular forms “a”, “an” and “the” are intended to include the pluralforms as well, unless the context clearly indicates otherwise. It willalso be understood that the term “and/or” as used herein refers to andencompasses any and all possible combinations of one or more of theassociated listed items. It will be further understood that the terms“includes,” “including,” “comprises,” and/or “comprising,” when used inthis specification, specify the presence of stated features, integers,steps, operations, elements, and/or components, but do not preclude thepresence or addition of one or more other features, integers, steps,operations, elements, components, and/or groups thereof.

As used herein, the term “if” may be construed to mean “when” or “upon”or “in response to determining” or “in response to detecting,” dependingon the context. Similarly, the phrase “if it is determined” or “if [astated condition or event] is detected” may be construed to mean “upondetermining” or “in response to determining” or “upon detecting [thestated condition or event]” or “in response to detecting [the statedcondition or event],” depending on the context.

FIG. 1 illustrates a schematic block diagram of a vehicle 100 whichcomprises an autonomous navigation system (ANS), according to someembodiments. Some or all of the ANS 110 illustrated in FIG. 1, includingone or more of the modules 111, 112, 113, etc., can be included in anyof the embodiments of ANSs included in any of the embodiments herein.

Vehicle 100 includes an autonomous navigation system (“ANS”) 110, a setof one or more sensor devices 116, a set of one or more control elements120, a set of one or more signal devices 117, and a set of one or moreuser interfaces 130. Sensor devices 116 include devices which monitorone or more aspects of an external environment in which the vehicle islocated. Monitoring an aspect of an external environment can includegenerating, at the sensor device, sensor data which includes informationregarding the aspect of the external environment. For example, a sensordevice 116 can include one or more of a camera device which generatesimages of one or more portions of the external environment, a light beamscanning device which generates one or more point clouds of one or moreportions of the external environments, a radar device which generatesradar data associated with one or more portions of the externalenvironment, etc. Aspects of an external environment which can bemonitored include one or more static elements, dynamic elements, etc.included in the environment. For example, a sensor device 116 whichincludes a camera device can capture images of an external environmentwhich includes images of static elements, including roadway laneboundary markers, roadway curbs, inanimate obstacles in the roadway,etc., images of dynamic elements including traffic participants, fauna,ambient environment conditions, weather, etc.

The control elements 120 included in vehicle 100 include various controlelements, including actuators, motors, etc. which each control one ormore components of the vehicle which cause the vehicle to be navigatedthrough an external environment. For example, a control element 120 caninclude one or more of a braking assembly (also referred to hereininterchangeably as a braking system) which applies braking pressure toone or more wheel assemblies of the vehicle to cause the vehicle to bedecelerated, a throttle assembly which adjusts the acceleration of thevehicle 100 through an external environment, a steering assembly whichadjusts one or more configurations of one or more wheel assemblies whichcauses the vehicle to be adjustably navigated in one or more variousdirections through the external environment, etc. A control element canexecute one or more various adjustments to navigation of the vehiclebased on receipt and execution of one or more various control commandsat the control elements from one or more of a user interface 130, theANS 110, etc.

The one or more user interfaces 130, also referred to hereininterchangeably as input interfaces, can include one or more drivingcontrol interfaces with which an occupant of the vehicle 100 caninteract, such that the driving control interfaces generate controlcommands which cause one or more control elements 130 to adjustablynavigate the vehicle 100, based on one or more occupant interactionswith one or more interfaces 140. In some embodiments, one or more inputinterfaces 140 included in the vehicle 100 provide one or more instancesof information to occupants of the vehicle, including indications ofwhether the vehicle is being navigated via autonomous driving control ofthe vehicle 100 by ANS 110, whether the vehicle is being navigated to astop based on implementation of a failure recovery plan at the ANS 110,whether at least one failure in the ANS 110 is determined to haveoccurred, etc.

Vehicle 100 includes at least one set of signal devices 117 which arecoupled to various portions of an exterior of the vehicle 100 and areconfigured, individually, collectively, in limited part, etc. togenerate one or more various targeted signals which are directed to oneor more particular dynamic elements in the external environment. In someembodiments, one or more signal devices are configured to generate atleast a portion of a targeted signal which communicates one or moreinstances of targeted information to the particular dynamic elements,where the one or more instances of targeted information are selectedbased at least in part upon one or more particular aspects of one ormore of the vehicle 100, the one or more dynamic elements in theexternal environment, etc. For example, a targeted signal cancommunicate, to a particular target dynamic element, information whichindicates a presence of the vehicle in the external environment. Inanother example, a targeted signal can communicate, to a particulartarget dynamic element, information which includes a message to thetarget dynamic element.

In some embodiments, a set of signal devices 117 included in a vehiclecan generate and direct a targeted signal to a particular target dynamicelement included in the external environment, so that the signal isdirected through a limited portion of the external environment in whichthe particular target dynamic element is located and the dynamicelements which can perceive the targeted signal can be at leastpartially restricted to the dynamic elements, including the particulartarget dynamic element, which are located in the limited portion of theexternal environment through which the targeted signal is directed.

In some embodiments, a targeted signal generated by one or more sets ofsignal devices 117 includes an audio signal and one or more sets ofsignal devices 117 are configured to generate one or more targeted audiosignals. For example, one or more signal devices 117 can include one ormore sets of speaker devices. In some embodiments, one or more speakerdevices can be adjustably positioned. The audio signal can include oneor more of an audio indication, an audio message, a particular soundeffect, some combination thereof, etc. The signal can be directedthrough a particular limited portion of the environment in which thetarget dynamic element is located via one or more of beamforming,ultrasonic modulation, etc. In some embodiments, vehicle 100 includesmultiple audio signal devices 117 located at various portions of theexterior of the vehicle 100, and, to generate a targeted audio signalwhich is directed at a target dynamic element, a limited selection ofthe audio signals which are located on a portion of the vehicle 100exterior and are at least partially oriented in a direction towards thetarget dynamic element can be commanded to collectively generate thetarget audio signal. One or more signal devices 117 can be adjustablypositioned to cause the signal devices 117 to be directed towards thetarget dynamic element, which results in a signal generated by thesignal devices to be directed towards the target dynamic element.

In some embodiments, a targeted signal generated by one or more sets ofsignal devices 117 includes a visual signal and one or more sets ofsignal devices 117 are configured to generate one or more targetedvisual signals. For example, one or more signal devices 117 can includeone or more sets of light generating devices, light indicators,light-emitting diodes (LEDs), headlight assemblies, etc. One or moresets of signal devices 117 which are configured to generate one or moretargeted visual signals can be adjustably positioned, so that one ormore sets of signal devices 117 can, individually, collectively, etc.,be positioned to direct one or more light beams towards one or moretarget dynamic elements in the external environment.

A message included in a targeted signal can be a warning associated withone or more of the driving route along which the vehicle is beingnavigated, one or more trajectories via which the dynamic element cannavigate through the environment, etc. For example, where a dynamicelement includes a pedestrian that is walking along a sidewalk proximateto a vehicle 100 and in a particular orientation which precludes thevehicle 100 from being within a field of view of the pedestrian, atargeted signal generated by one or more signal devices 117 which isdirected to the pedestrian can include an audio warning, to thepedestrian, to avoid turning into the roadway along which the vehicle isbeing navigated. The message can include a verbal, spoken message.

In some embodiments, one or more instances of personal data can beaccessed by ANS 110. For example, in some embodiments, ANS 110 canprocess sensor data, generated by one or more sensor devices 116, and,based on personal data including facial recognition data, associateduser device detection, etc., identify a dynamic element in theenvironment as an element associated with a particular individual, useraccount, etc. In some embodiments, the content included in a targetedsignal generated at one or more signal devices 117 includes contentgenerated based on one or more instances of personal data, includingpersonal schedule data, identity data, etc. For example, where a dynamicelement is identified at ANS 110 as being a particular individual, theANS can generate a targeted signal which includes audio content whichaddresses the dynamic element by name.

Users can benefit from use of personal data by the ANS. For example, thepersonal data can be used to communicate relevant content to aparticular individual identified in the external environment by the ANS.Accordingly, use of such personal data enables users to influence andcontrol delivered content.

Users can selectively block use of, or access to, personal data. Asystem incorporating some or all of the technologies described hereincan include hardware and/or software that prevents or blocks access tosuch personal data. For example, the system can allow users to “opt in”or “opt out” of participation in the collection of personal data orportions of portions thereof. Also, users can select not to providelocation information, or permit provision of general locationinformation (e.g., a geographic region or zone), but not preciselocation information.

Entities responsible for the collection, analysis, disclosure, transfer,storage, or other use of such personal data should comply withestablished privacy policies and/or practices. Such entities shouldsafeguard and secure access to such personal data and ensure that otherswith access to the personal data also comply. Such entities shouldimplement privacy policies and practices that meet or exceed industry orgovernmental requirements for maintaining the privacy and security ofpersonal data. For example, an entity should collect users' personaldata for legitimate and reasonable uses, and not share or sell the dataoutside of those legitimate uses. Such collection should occur onlyafter receiving the users' informed consent. Furthermore, third partiescan evaluate these entities to certify their adherence to establishedprivacy policies and practices.

ANS 110 includes various modules 111, 112, 113 which can be implementedby one or more computer systems. ANS 110 autonomously navigates vehicle100 along one or more driving routes, based at least in part upon sensordata generated by one or more sensor devices 116.

Driving control module 112 can determine a driving route based at leastin part upon at least some sensor data generated by one or more sensordevices 116, including position data indicating a geographic position ofthe vehicle 100 and a world model, stored in one or more memory storagedevices included in the vehicle 100, one or more remotely-locatedsystems external to the vehicle 100, etc.

In some embodiments, the ANS 110 determines a driving route based atleast in part upon occupant interaction with one or more interfaces 130included in the vehicle 100, including one or more interactions whichresult in the ANS 110 receiving an occupant-initiated command tonavigate the vehicle 100 from a particular location in the externalenvironment, which can include a present location of the vehicle 100 inthe external environment, to a particular destination location. In someembodiments, the occupant-initiated command includes a command tonavigate the vehicle 100 along a particular occupant-selected drivingroute. In some embodiments, the ANS 110 receives a driving route from aremotely-located system via one or more communication networks.

In some embodiments, the module 112 generates one or more sets ofcontrol elements commands which are communicated to one or more controlelements 120 in the vehicle 100 and cause the control elements 120 tonavigate the vehicle 100 along a driving route. The module 112 cangenerate control commands based on a driving route, where the controlcommands, when executed by the control elements 120, cause the vehicle100 to be navigated along the driving route.

ANS 110 includes an intention recognition module 111 which generates adriving route through a portion of an external environment based atleast in part upon predicted trajectories of one or more dynamicelements, including one or more traffic participants, instances offauna, pedestrians, etc., through at least a portion of the externalenvironment. The module 111 can process sensor data, generated by one ormore sensor devices 116, and, based on the processing, identify variousstatic elements and dynamic elements in the external environment.

The module 111 can identify various features of the various staticelements and dynamic elements. The various features are referred toherein as contextual cues and include object cues which are associatedwith observed aspects of a dynamic element and situational cues whichare associated both the dynamic element and various aspects of theenvironment, including interactions between dynamic element and variouselements in the environment, motions of the dynamic element with regardto various elements in the environment, etc. An object cue associatedwith a dynamic element can include one or more particular featuresassociated with an appearance of one or more portions of a dynamicelement detected via processing of sensor data, one or more particularfeatures associated with various movements and actions of the dynamicelement in the environment detected via processing of sensor data, etc.For example, where a pedestrian is detected, via sensor data processing,to be jogging along a sidewalk which extends adjacent to a roadway,object cues which can be identified via sensor data processing caninclude a type of clothing worn by the pedestrian, a rate of motion bythe pedestrian along the sidewalk, an orientation of the pedestrian anddirection of travel, a position, velocity, acceleration, etc. of thepedestrian with regard to one or more particular static elements,dynamic elements, etc. in the environment, an interaction by thepedestrian with one or more static elements, dynamic elements, etc. inthe environment, etc. In another example, situational cues can include apresent set of weather conditions in the environment in which thedynamic element is moving, a position, motion, etc. of the dynamicelement relative to one or more particular static elements in theenvironment, including one or more particular structures, in theenvironment, etc.

Module 111 can predict a trajectory of a dynamic element, including atraffic participant, through the environment based on identifyingvarious contextual cues associated with the dynamic element andcorrelating the identified cues with one or more sets of cues includedin an association between the sets of cues and one or more particulardynamic element intentions. Correlating the identified cues with cuesincluded in an association can include determining an at least partialmatch between the identified contextual cues and a set of cues includedin the association, where an at least partial match can include a matchbetween the sets of cues which exceeds a certain threshold level. Basedon the correlation, module 111 can associate the identified cues with anintention included in the association.

Associating identified cues, associated with a dynamic element, with aparticular intention can include associating the particular intentionwith the dynamic element. A dynamic element intention can include a setof specified actions, motions, etc. which the dynamic element ispredicted to take, based on at least partial identification of aparticular set of contextual cues associated with the dynamic element.Associating a set of identified contextual cues with a particularintention can result in a prediction, at module 111, that a dynamicelement identified in the environment and associated with the intentionwill take the set of actions specified in the particular intention.

Based on associating a dynamic element with a particular intention,module 111 can generate a predicted trajectory of the dynamic elementthrough the external environment, where the trajectory indicates apredicted position, velocity, acceleration, etc. of the dynamic elementat various future times in the external environment. Based on thepredicted trajectory of the dynamic element through the environment,module 111 can generate a driving route along which vehicle 100 can benavigated which results in the vehicle 100 avoiding intersection withthe dynamic element navigation according to the predicted trajectory.

ANS 110 includes signaling module 113 which generates commands tovarious signal devices 117 which cause the various devices 117 togenerate one or more targeted signals which are directed at targetdynamic elements in the external environment. Generating commands atmodule 113 can include selecting particular target dynamic elements,determining a direction, the angle and axis of the signal transmissionthrough the external environment, the information included in thesignal, etc. Module 113 can select a targeted dynamic element determineto generate a targeted signal to the target dynamic element, determinethe particular content to be communicated to the dynamic element via thetargeted signal, etc. based on determinations at one or more of modules111, 112 in ANS 110. For example, where module 111 identifies a dynamicelement in the external environment which includes a pedestrianapproaching the roadway, where the vehicle 100 is determined to beoutside a field of view of the pedestrian, module 113 can, in responseto the identification and determination at module 111 by determining togenerate a targeted signal to the pedestrian, determining a particularaxis and angle of the signal transmission which at least partiallyrestricts the signal from being received by dynamic elements other thanthe pedestrian, selecting a set of devices 117 which can collectivelygenerate a signal with the determined axis and angle, determining thecontent of the signal, and commanding the selected set of devices 117 togenerate the targeted signal which includes the determined content andis transmitted along the determined axis and angle. In the aboveexample, module 113 can determine that the content to include in thetargeted signal includes an audio warning message, so that the module113, in commanding a set of devices 117 to generate the targeted signalto the pedestrian, commands the devices 117 to generate a targeted audiosignal which includes a particular warning message to the pedestrianregarding a risk of paths intersecting with the vehicle.

FIG. 2 illustrates an overhead view of an environment in which multipledynamic elements are located, including a vehicle which is autonomouslynavigated through the environment and includes a set of sensors whichcan generate sensor data associated with the dynamic elements and anautonomous navigation system which can determine a particular predictedtrajectory of a dynamic element based on contextual cues identified inthe sensor data, according to some embodiments. Vehicle 210 can includeany of the embodiments of vehicles included herein, and ANS 212 caninclude any of the embodiments of ANSs included herein.

In some embodiments, an ANS included in a vehicle processes sensor data,generated by various sensor devices included in the vehicle, andidentifies at least one particular dynamic element included in theenvironment. For example, in the illustrated embodiment, where vehicle210 is located in an external environment 200 which includes a roadway250 with lanes 252, 254 and sidewalks 260A-B extending alongside theroadway 250, sensor devices 213 included in the vehicle 210 can generatesensor data which can be processed by the ANS 212 so that the ANS, as aresult, determines that the vehicle 210 is located in lane 252 of theroadway 250 and that a dynamic element 230, which can include apedestrian, is located at a particular position on the sidewalk 260B andis moving at a particular velocity 232 along the sidewalk 260B.

In some embodiments, an ANS included in a vehicle determines variousfeatures of a dynamic element and the external environments in which adynamic element is located. The ANS can associate these features,referred to as dynamic element contextual cues, with the dynamicelement. For example, in the illustrated embodiment shown in FIG. 2, ANS212, based on processing data generated by sensors 213, can identifycontextual cues including a cue indicating that a dynamic element 230 islocated in environment 200 at a certain time of day, a cue indicatingthat a dynamic element 230 is located in a particular type ofenvironment (e.g., rural, urban, residential area, industrial area,etc.), a proximity of various specific structures (e.g., schools,landmarks, etc.) to the element 230, a geographic position of theelement 230 relative to various static elements, dynamic elements, etc.located in the environment 200, etc. In one example, the contextual cueswhich can be identified by the ANS 212 and associated with element 230can include an identification that element 230 is remotely located fromany crosswalks, bridges, etc. via which the dynamic element 230 mighttravel across the roadway 250. In another example, ANS 212 can identifya cue that the element 230 is moving through an environment 200 which isa rural environment, etc.

ANS 212 can determine, based on processing sensor data associated withthe dynamic element 230, contextual cues associated with element 230which indicate one or more of a visual appearance of the dynamic element230, a type of traffic participant of the dynamic element 230, etc. Forexample, ANS 212 can identify cues associated with element 230, based onprocessing sensor data generated by one or more sensors 213, thatindicate that element 230 is a pedestrian and that the pedestrian 230 iswearing a particular type of clothing, including a set of clothingassociated with exercise. Such determination can include utilizingcaptured images of the dynamic element 230 and comparing an appearanceof the element 230 with representations of various particular articlesof clothing. In another example, ANS 212 can identify a cue whichindicates that element 230 is a pedestrian who is utilizing a wheelchairfor mobility.

In some embodiments, where the dynamic element 230 is a trafficparticipant, including a pedestrian, vehicle, etc. the ANS 212 canprocess sensor data associated with the traffic participant anddetermine, based on the processing, a cue which indicates a field ofview of the traffic participant. As shown, ANS 212 can determine that apresent field of view of the dynamic element 230 is as shown at 234. ANS212 can identify, as a contextual cue, that the field of view 234 isapproximately centered on the sidewalk 260B along which the dynamicelement 230 is moving 232. The ANS can identify, as a contextual cue,that the dynamic element 230 is moving along a particular velocity 232and acceleration.

The ANS can associate identified contextual cues with the dynamicelement 230, based on an association of the cues with monitoring thedynamic element. For example, a contextual cue indicating an appearanceof a dynamic element 230 can be associated with that element 230 basedon the cue being identified based on monitoring the appearance of thedynamic element, and a contextual cue indicating that a dynamic element230 is moving through a particular type of environment can be associatedwith the element 230 based on the cue being identified based at least inpart upon monitoring the motion of the element 230 through one or moreexternal environments.

Based on the identified contextual cues associated with a dynamicelement, ANS 212 can determine a correlation between at least some ofthe identified contextual cues with a set of contextual cues which areassociated with a particular dynamic element intention. Based ondetermining the correlation, the ANS 212 can associate the dynamicelement 230 with the particular dynamic element intention and cangenerate a predicted trajectory of the dynamic element 230 based on theassociated particular dynamic element intention.

In the illustrated embodiment, ANS can determine that the identifiedcontextual cues associated with the dynamic element 230 correlate with aset of contextual cues associated with a particular dynamic elementintention, where the particular intention specifies that the dynamicelement is predicted to continue moving along the sidewalk on which itis presently moving. ANS 212 can associate the particular intention withdynamic element 230 and generate a predicted trajectory 236 of thedynamic element 230 based on the particular intention associated withthe dynamic element 230. In some embodiments, ANS 212 can generatevarious different predicted trajectories 237A-C of the dynamic element230 based on different contextual cues identified in association withboth the dynamic element 230 and the environment 200, differentintentions which correlate to the identified cues, etc.

As shown, ANS 212 generates a driving route 240 along which vehicle 210is navigated to at least position 241 based at least in part upon thepredicted trajectory 236 of the dynamic element 230. Because thepredicted trajectory 236 continues along sidewalk 260B, the ANS 212generates a route 240 which continues along lane 252 without substantialdeviation in direction, velocity, etc. In another example, where thepredicted trajectory of element 230 is determined to be trajectory 237Cwhich veers from sidewalk 260B into the roadway lane 252 along whichvehicle 210 is presently moving, the ANS 212 can generate a differentdriving route which navigates the vehicle 210 to avoid intersecting withtrajectory 237C, including a route via which vehicle 210 is decelerated,navigates at least partially out of lane 252, some combination thereof,etc.

FIG. 3 illustrates an overhead view of an environment in which multipledynamic elements are located, including a vehicle which is autonomouslynavigated through the environment and includes a set of sensors whichcan generate sensor data associated with the dynamic elements and anautonomous navigation system which can determine a particular predictedtrajectory of a dynamic element based on contextual cues identified inthe sensor data, according to some embodiments. Vehicle 310 can includeany of the embodiments of vehicles included herein, and ANS 312 caninclude any of the embodiments of ANSs included herein.

In the illustrated embodiment, where vehicle 310 is located in anexternal environment 300 which includes a roadway 350 with lanes 352,354 and sidewalks 360A-B extending alongside the roadway 350, sensordevices 313 included in the vehicle 310 can generate sensor data whichcan be processed by the ANS 312 so that the ANS, as a result, determinesthat the vehicle 310 is located in lane 352 of the roadway 350 and thata dynamic element 330, which can include a pedestrian, is located at aparticular position on the sidewalk 360B.

The ANS 312 can identify, as environmental contextual cues associatedwith environment 300 based on processing data generated by sensors 313,that environment 300 includes sidewalks 360A-B on opposite adjacentsides of roadway 350 and that a crosswalk 356 extends across the roadway350 between the sidewalks 360A-B.

The ANS 312 can further identify dynamic element contextual cuesassociated with the dynamic element 330 which indicate that the dynamicelement is positioned at a stop, that the dynamic element is positionedproximate to the sidewalk 356 across the roadway 350, and that thedynamic element 330 has a field of view 334 which includes the crosswalk356 and does not include sidewalk 360 on which dynamic element 330 islocated.

ANS 312 can determine that the set of identified dynamic element cuesassociated with element 330 correlate with a set of contextual cuesincluded in a particular intention association. Determining acorrelation between the contextual cues can include determining that theset of identified contextual cues at least partially matches the set ofcontextual cues included in the association. The ANS 312 can determinethat the association includes an association of the set of contextualcues with a particular dynamic element intention which specifies that,although the dynamic element is presently stationary, the dynamicelement is predicted to move onto the crosswalk and across the roadwayvia the crosswalk.

Based on associating the dynamic element 330 with a particular dynamicelement intention which specifies that, although the dynamic element ispresently stationary, the dynamic element is predicted to move onto thecrosswalk and across the roadway via the crosswalk, ANS 312 can generatea predicted trajectory 336 of the dynamic element 330 through theenvironment 300, where the predicted trajectory 336 of the dynamicelement 330 passes along crosswalk 356 and across roadway 350, accordingto the particular dynamic element intention associated with the dynamicelement 330.

In some embodiments, ANS 312, in generating a predicted trajectory of adynamic element through an environment, selects one of a set ofpredicted trajectories based on a particular dynamic element intentionassociated with the dynamic element. A set of trajectories can beassociated with a dynamic element based on a dynamic element typeassociated with the dynamic element. For example, in the illustratedembodiment, a set of trajectories 336, 337A-B can be associated withdynamic element 330 based on dynamic element 330 being a pedestrian, andANS 312 can select trajectory 336 as the predicted trajectory of dynamicelement 330, rather than one of trajectories 337A-B, based ondetermining a correlation between the trajectory 336 and the particulardynamic element intention which is associated with the dynamic element330.

ANS 312 can generate a driving route 341 along which vehicle 310 isnavigated based at least in part upon the predicted trajectory 336 ofthe dynamic element 330 through the environment 300. The driving routecan be configured to navigate the vehicle 310 in avoidance of anintersection with the predicted trajectory of the dynamic element 330.In the illustrated embodiment, ANS 312 generates a driving route 341which, when vehicle 310 is navigated along the route 341, results in thevehicle being decelerated to a position 342 concurrently with thepredicted position of dynamic element 330 being at one or more positionsalong trajectory 336 which is located on a portion of crosswalk 356which is within lane 352.

In some embodiments, route 341 is configured to navigate the vehicle 310along a pathway which intersects a portion of the trajectory 336subsequently to the dynamic element travelling through the portion ofthe trajectory 336, so that the vehicle 310 navigates “behind” thedynamic element 330 as it navigates through the environment 300. Forexample, ANS 312 can generate a route 341, based on the predictedtrajectory 336, which includes decelerating vehicle 310 to a position342 for a period of time and subsequently accelerating the vehicle,along lane 352, across the pathway of trajectory 336, based on adetermination that dynamic element 330 has moved along trajectory 330out of lane 352 and into at least lane 354.

In some embodiments, ANS is configured to continue monitoring variousaspects of the environment 300, including movement of the dynamicelement 330 through the environment 300, subsequent to generating thepredicted trajectory 336 of the element 330 and generating a drivingroute 341 of the vehicle 310 based thereupon. The ANS 312 can determinewhether the dynamic element 330 is moving along the predicted trajectory336. In some embodiments, ANS 312 responds to a determination that thedynamic element 330 is following a different trajectory than thepredicted trajectory by revising the driving route 341 via which vehicle310 is navigated through the environment. ANS 312 can revise theassociation between the identified contextual cues associated with thedynamic element 330 and the environment 300 with a particular intentionbased on determining that the dynamic element moves along a trajectorywhich is separate from a predicted trajectory generated based on theparticular intention. Such a revision of the association can includeadjusting a confidence level associated with the association, adjustingthe particular intention to specify a different set of predicted dynamicelement movements, some combination thereof, etc.

FIG. 4 illustrates an overhead view of an environment in which multipledynamic elements are located, including a vehicle which is autonomouslynavigated through the environment and includes a set of sensors whichcan generate sensor data associated with the dynamic elements and anautonomous navigation system which can determine a particular predictedtrajectory of a dynamic element based on contextual cues identified inthe sensor data, according to some embodiments. Vehicle 410 can includeany of the embodiments of vehicles included herein, and ANS 412 caninclude any of the embodiments of ANSs included herein.

In the illustrated embodiment, where vehicle 410 is located in anexternal environment 400 which includes a roadway 450 with lanes 452,452 and sidewalks 460-B extending alongside the roadway 450, sensordevices 413 included in the vehicle 410 can generate sensor data whichcan be processed by the ANS 412 so that the ANS, as a result, determinesthat the vehicle 410 is located in lane 452 of the roadway 450. The ANS412 further determines that static element 420 and dynamic elements 430,432A-C, and 434 are located in the environment 400. Dynamic elements430, 432A-C can include traffic participants which include vehicleslocated on at least a portion of roadway 450. Dynamic elements 434 caninclude pedestrians. Static element 420 can include a particularstructure.

The ANS 412 can identify, as contextual cues associated with one or moreof elements 430, 432, 434 based on processing data generated by sensors413, that the dynamic elements are located proximate to a static element420 which is a particular structure. For example, the ANS 412 canidentify that structure 420 is a school building and that elements 434,430, 432 are located proximate to the school building. In someembodiments, ANS 412 can identify a contextual cue that the vehicle 410and elements 430, 432, 434 are located in a school zone, based at leastin part upon determining that the present geographic position of thevehicle and dynamic elements, determined based on processing sensor datagenerated by a sensor device 413, correlates with a determinedgeographic location associated with a school zone located in theenvironment 400, a particular school zone, some combination thereof,etc. The geographic location associated with a school zone, a particularschool zone, some combination thereof, etc. can be determined based oninformation received from a service, system, etc. which is locatedremotely from the vehicle 410, where the information is received atvehicle 410 via one or more communication networks. The ANS 412 canidentify a contextual cue that indicates that one or more of the vehicle410, elements 430, 432, 434, etc. are located in a school zone based atleast in part upon determining, based on processing sensor data, thatstatic element 420 is a school structure associated with a school zoneand that one or more of vehicle 410, dynamic elements 430, 432, 434,etc. is located within a certain threshold distance from the staticelement 420.

In some embodiments, the ANS 412 can identify, as a contextual cueassociated with one or more of the dynamic elements 430, 432, 434, etc.based on processing data generated by sensors 413, that the one or moredynamic elements are located in environment 400, within a certainproximity of the school 420, at a time which is included within aparticular time period during which classes at the school 420 aredismissed. The identification can be based on determining a presenttime, determining a set of events associated with the identified school420, where at least one event includes class dismissal, comparing thepresent time with a time period associated with the class dismissalevent, and determining that the present time is located within the timeperiod associated with the class dismissal event.

ANS 412, based on processing sensor data generated by sensors 413, canidentify contextual cues associated with at least elements 432 whichindicate that dynamic elements 432A-C are vehicles which are stoppedproximate to respective sides of the roadway 450, also referred toherein as being “pulled-over” to the sides of the roadway 450, and canfurther identify contextual cues associated with at least elements 424which indicate that dynamic elements 434, which include pedestrians, aremoving 435 in a general direction away from the static element 420 whichis identified as a school building and towards the roadway 450. ANS 412can identify contextual cues associated with each of the dynamicelements 434 which include identifying the dynamic elements 434 aschildren.

In some embodiments, dynamic element cues associated with one or moreparticular dynamic elements in an environment are associated with one ormore other separate dynamic elements in the environment. For example,ANS 412 can associate the dynamic element cues identified based onmonitoring the vehicle dynamic elements 430, 432A-C with the dynamicelements 434 and can further associate the dynamic elements cuesidentified based on monitoring the children dynamic elements 434 withthe dynamic elements 430, 432A-C.

Based on identifying the various contextual cues associated with thevarious dynamic elements in the environment 400, ANS 412 can correlatethe cues associated with one or more dynamic elements with one or moresets of contextual cues included in a particular intention associationwhich associates the one or more sets of contextual cues with one ormore particular dynamic element intentions. In the illustratedembodiment, ANS 412 can associate each of the vehicles 432A-C with aparticular dynamic element intention which specifies that the dynamicelements are predicted to remain stopped at the sides of the roadway450, based on matching at least a portion of the dynamic element cuesassociated with the elements 432A-C with a set of contextual cues whichare themselves associated with the particular dynamic element intention.Based on associating each of the vehicles 432A-C with a particulardynamic element intention which specifies that the dynamic elements arepredicted to remain stopped at the sides of the roadway 450, ANS 412generates a predicted trajectory for each of the vehicles 432A-C whichincludes the vehicles 432A-C remaining stationary for at least a periodof time, as shown in FIG. 4.

In addition, ANS 412 can associate vehicle 430 with a particular dynamicelement intention which specifies that the dynamic element is predictedto pull over to the side of the roadway and stop, based on matching atleast a portion of the dynamic element cues associated with the elements430 with a set of contextual cues which are themselves associated withthe particular dynamic element intention. ANS 412 can, based on theintention associated with the vehicle 430, generate a predictedtrajectory 431 for the vehicle 430 which passes to the side of theroadway and stops, as shown in FIG. 4.

In some embodiments, a contextual cue associated with a dynamic elementindicates movements of the dynamic element relative to movements ofother dynamic elements in the environment. As a result of identifyingcues which incorporate movements of various other dynamic elements inthe environment, ANS 412 can associate a given dynamic element with anintention which more accurately predicts future movements of the dynamicelement through the environment than via generating cues whichincorporate movement of the given dynamic element alone. For example, inthe illustrated embodiment, ANS 412, based on identifying that thevehicle 430 is moving slowly along lane 452 in a school zone during atime of day during which classes are dismissed from school 420 proximateto vehicle 430 without incorporating motions and positions of ofchildren 434 and vehicles 432A-C in the environment 400, ANS 412 mayassociate vehicle 430 with a different intention which specifies thatthe vehicle 430 is predicted to continue moving along lane 452, ratherthan pull over to the side of roadway 450.

In addition, ANS 412 can associate dynamic elements 434 with aparticular dynamic element intention which specifies that the dynamicelements 434 are predicted to continue moving into the roadway 450towards proximate stopped vehicles 432, based on matching at least aportion of the dynamic element cues associated with elements 434 with aset of contextual cues which are themselves associated with theparticular dynamic element intention. As a result, ANS 412 can generatepredicted trajectories 436 of the elements 434 which pass towards thevehicles 430, 432A-C and across sidewalk 460B and into the roadway 450.In some embodiments, ANS 412 identifies contextual cues associated withdynamic elements 434 which indicate movement of the elements 434relative to particular movements of one or more additional dynamicelements through the environment 400.

In some embodiments, an ANS generates a driving route configured tonavigate the vehicle along a pathway which avoids intersection of thevehicle with predicted trajectories of multiple dynamic elements in anenvironment. As shown, ANS 412 generates a driving route 441, based onpredicted trajectories 431, 436 of dynamic elements 430, 434, whichdecelerates vehicle 410 so that, as a result, the vehicle 410 avoidsintersections with trajectories 431, 436 at more than a particularthreshold rate of speed. The ANS 412 can further control navigation ofthe vehicle 412 along the route to avoid paths intersecting with thevarious dynamic elements 434, 430, 432 included in the environment inresponse to deviations of the dynamic elements from the predictedtrajectories of the dynamic elements.

FIG. 5 illustrates generating an intention association betweenidentified contextual cues and subsequent predicted dynamic elementmovements, according to some embodiments. The generating can beimplemented by one or more portions of any embodiment of ANS included inany embodiments herein. An ANS can be implemented by one or morecomputer systems.

At 502, one or more instances of sensor data 501 are received from oneor more sensor devices included in a vehicle. Sensor data can includevarious instances of information regarding one or more portions of anexternal environment in which the vehicle is located. For example,sensor data generated by a sensor device can include images, of at leasta portion of an external environment, generated by a camera device, apoint cloud, of a portion of an external environment, generated by alight beam scanning device, a radar image of an environment generated bya radar device, position information generated by a geographicpositioning sensor device, weather data generated by one or more weathersensor devices, ambient light data generated by one or more ambientlight sensors, time data generated by one or more chronometers, etc.

At 504, received sensor data is processed. Processing sensor data caninclude identifying various static elements, dynamic elements, somecombination thereof, etc. included in the external environment. Forexample, where an external environment in which a vehicle is locatedincludes a roadway on which the vehicle is located, a building proximateto the roadway processing sensor data generated by sensor devicesincluded in the vehicle can include identifying the building as aparticular static element in the environment, where the identificationcan include determining a particular position of the building in theenvironment, a particular distance between the building and the vehicle,a particular type of static element associated with the building, etc.In another example, where the external environment in which the vehicleis located a pedestrian standing ahead of the vehicle adjacent to theroadway, processing sensor data generated by sensor devices included inthe vehicle can include identifying the pedestrian as a particulardynamic element in the environment, where the identification can includedetermining a particular position of the pedestrian in the environment,a particular orientation of the pedestrian, determining a particularpresent velocity, acceleration, etc. of the pedestrian, etc.

At 506, one or more contextual cues associated with one or more of thedynamic elements are identified based on processing sensor data at 504.Identifying a contextual cue from processing sensor data of a particulardynamic element, static element, etc. can include associating theidentified contextual cue with one or more particular dynamic elements.As a result, the identifying at 506 can result in identifying variousdynamic element object contextual cues 507A and situational contextualcues 507B associated with various dynamic elements in the environment.

Contextual cues identified and associated with an element in anenvironment can include “object contextual cues” 507A which areidentified based on processing sensor data generated based on monitoringone or more features of the element and “situational contextual cues”which are identified based on processing sensor data generated based onmonitoring the element relative to one or more elements of theenvironment, including motions, positions, orientations, etc. of theelement relative to one or more aspects of one or more dynamic elementslocated in the environment, one or more aspects of one or more staticelements located in the environment, one or more aspects of theenvironment in general, some combination thereof, etc.

For, example, where a vehicle is moving along a roadway, and where adynamic element which includes a pedestrian is moving along a sidewalkwhich extends adjacent to the roadway, identifying 506 object contextualcues 507A associated with the pedestrian can include identifying objectcontextual cues which can include a cue indicating that the pedestrianis clothed in running exercise-related attire, a cue indicating that thepedestrian is wearing audio headset gear, etc. Identifying 506contextual cues 507B associated with the pedestrian can includeidentifying situational contextual cues which include a cue indicatingthat the pedestrian is moving along a sidewalk with a general directionof travel which extends along in the sidewalk, a cue indicating that thepedestrian is moving along the sidewalk within a certain thresholdvelocity associated with jogging activities, a cue indicating that afield of view of the pedestrian includes the sidewalk and generaldirection of pedestrian travel, etc.

In another example, where a vehicle is moving along a roadway whichextends proximate to a static element which includes a school building,and dynamic elements in the environment include a vehicle parked at theside of the road proximate to the school building and a child which ismoving from the school building towards the roadway, identifying 506contextual cues 507B associated with the child can include identifyingsituational contextual cues which can include a cue indicating that thechild is proximate to a static element which is a portion of aparticular school, a cue indicating that the child is moving away fromthe static element which is part of a particular school towards theroadway, and a cue indicating that the child is located proximate to theparticular school at a time is within a time period associated withclass dismissal at the particular school. Identifying 506 contextualcues 507A associated with the dynamic element which includes the childcan include an object contextual cue indicating that the dynamic elementis a child, an object contextual cue indicating that the child iswearing a backpack.

At 508, subsequent dynamic element motion is monitored via processingsensor data 501 generated by one or more sensor devices. For example,where the vehicle is moving along the roadway where a pedestrian ismoving along an adjacent sidewalk, the monitoring at 508 includesmonitoring subsequent motions of the pedestrian subsequent toidentifying the various contextual cues at 506.

At 510, based on monitoring the subsequent dynamic element motion at508, a dynamic element intention is generated, where the intentionspecifies occurrence of the motion of the dynamic element, monitored at508, subsequent to identification, at 506, of the contextual cuesassociated with the dynamic element. For example, where a pedestrian ismonitored, at 508, to continue moving along a sidewalk subsequent toidentification of cues at 506 which indicate that the pedestrian ismoving within a velocity window associated with jogging activities, iswearing jogging attire, has a field of view which includes the sidewalkand the direction of travel, etc., an intention generated at 510 canspecify that the pedestrian is predicted to continue moving along thesidewalk subsequent to identifying the cues identified at 506.

In another example, where a child is monitored, at 508, to continuemoving away from a school structure and out into a roadway, subsequentto identification of cues indicating that the dynamic element is achild, that the child is wearing a backpack, that the child is movingaway from a school, that the child is moving away from the school at atime which is within a time period associated with class dismissal at aschool, that the child is moving towards a roadway, some combinationthereof, etc., an intention can be generated which specifies that thechild is predicted to move into the roadway subsequent to identificationof the cues at 506.

At 512, the intention generated at 512 is associated with at least someof the particular cues, identified at 506, which are associated with thedynamic element and upon which the intention is based. As a result,identifying some or all of the particular cues associated with anotherdynamic element at a future point in time can result in a correlation ofthe other dynamic element with the associated dynamic element intention.

FIG. 6 illustrates autonomously navigating a vehicle through an externalenvironment based on a predicted trajectory of a dynamic element in theexternal environment, according to some embodiments. The generating canbe implemented by one or more portions of any embodiment of ANS includedin any embodiments herein. An ANS can be implemented by one or morecomputer systems.

At 602, one or more instances of sensor data 601 are received from oneor more sensor devices included in a vehicle. Sensor data can includevarious instances of information regarding one or more portions of anexternal environment in which the vehicle is located. For example,sensor data generated by a sensor device can include images, of at leasta portion of an external environment, generated by a camera device, apoint cloud, of a portion of an external environment, generated by alight beam scanning device, a radar image of an environment generated bya radar device, position information generated by a geographicpositioning sensor device, weather data generated by one or more weathersensor devices, ambient light data generated by one or more ambientlight sensors, time data generated by one or more chronometers, etc.

At 604, received sensor data is processed. Processing sensor data caninclude identifying various static elements, dynamic elements, somecombination thereof, etc. included in the external environment. Forexample, where an external environment in which a vehicle is locatedincludes a roadway on which the vehicle is located, a building proximateto the roadway processing sensor data generated by sensor devicesincluded in the vehicle can include identifying the building as aparticular static element in the environment, where the identificationcan include determining a particular position of the building in theenvironment, a particular distance between the building and the vehicle,a particular type of static element associated with the building, etc.In another example, where the external environment in which the vehicleis located a pedestrian standing ahead of the vehicle adjacent to theroadway, processing sensor data generated by sensor devices included inthe vehicle can include identifying the pedestrian as a particulardynamic element in the environment, where the identification can includedetermining a particular position of the pedestrian in the environment,a particular orientation of the pedestrian, determining a particularpresent velocity, acceleration, etc. of the pedestrian, etc.

At 606, one or more contextual cues associated with one or more of thedynamic elements located in the environment are identified based onprocessing sensor data at 604. Identifying a contextual cue fromprocessing sensor data of a particular dynamic element, static element,etc. can include associating the identified contextual cue with theparticular dynamic element. As a result, the identifying at 606 canresult in identifying various dynamic element contextual cues whichinclude object contextual cues 607A and situational contextual cues 607Bassociated with one or more various dynamic elements in the environment.

At 610, at least some of the identified contextual cues 607A, 607Bassociated with a dynamic element in the environment are compared tocontextual cues included in one or more various contextual intentionassociations 608, which can result in determining a correlation betweenat least some of the cues 607A-B with a set of contextual cues includedin at least one particular association 608. Determining a correlationbetween at least some cues 607A-B identified at 606 with a set of cuesincluded in an association, also referred to herein as determining thatat least some cues 607A-B identified at 606 correlate with a set of cuesincluded in an association, can include at least partially matching thecues 607A-B with the set of cues included in the association above acertain threshold level. For example, matching five of the identifiedcues 607A-B associated with a dynamic element with five cues out of aset of six cues included in a particular association 608 can result in adetermination of a correlation of the five identified cues 607A-B withthe particular association 608. An association 608 includes a set ofcontextual cues associated with one or more dynamic elements and acorresponding dynamic element intention, associated with the set ofcontextual cues, which specifies a prediction of the motion of the oneor more dynamic elements through the environment based on the set ofcontextual cues.

At 612, based on correlating at least some identified cues 607A-Bassociated with a dynamic element in the environment with a particularassociation 608, the dynamic element is associated with a dynamicelement intention included in the particular association 608. As aresult, the intention included in the particular association 608 isdetermined to be a prediction of the motion of the dynamic elementthrough the environment, based on the at least some identified cues607A-B.

At 614, a trajectory of the dynamic element through the environment isdetermined, based at least in part upon the dynamic element intentionassociated with the dynamic element at 612. The trajectory can specify aparticular variation of one or more of the position, velocity,acceleration, etc. of the dynamic element through the environment basedon time. As a result, the generated trajectory can illustrate aprediction of the route along which the dynamic element is predicted tomove through the environment and the various points in the environmentat which the dynamic element is predicted to be located, along theroute, at various points in time.

At 616, a driving route of the vehicle through the environment isgenerated based at least in part upon the predicted trajectory of thedynamic element through the environment. The driving route can be atrajectory of the vehicle which avoids intersection with one or morepredicted trajectories of one or more dynamic elements through theenvironment where the vehicle and the one or more dynamic elements arelocated within a particular threshold proximity distance at one or moregiven points in time. A driving route can be a route through theenvironment which avoids navigating the vehicle within a certaindistance of any dynamic elements navigating through the environmentalong predicted trajectories of the various dynamic elements.

FIG. 7 illustrates an overhead view of an environment in which multipledynamic elements are located, including a vehicle which is autonomouslynavigated through the environment and includes a set of indicators whichcan generate a set of targeted signals which are transmitted to specificdynamic elements in the external environment, according to someembodiments. Vehicle 710 can include any of the embodiments of vehiclesincluded herein, and ANS 712 can include any of the embodiments of ANSsincluded herein.

In some embodiments, a vehicle includes one or more sets of signalgenerators which can be commanded by an ANS included in the vehicle togenerate one or more targeted signals which are directed to one or moreparticular target elements included in the external environment in whichthe vehicle is located. A targeted signal can include a signal which istransmitted along a particular selected angle and axis which results inthe signal passing through a restricted portion of the externalenvironment in which the target element is located, so that the signalis at least partially restricted from being received at one or moreother elements included in the environment. A targeted signal which isdirected at a particular target element in the environment can includeone or more particular instances of information, including one or moreparticular messages, which is at least partially associated with thetarget element. In some embodiments, a target signal includesinformation which is selected, at the ANS included in a vehicle, basedat least in part upon a predicted trajectory of the target elementthrough the external environment.

In some embodiments, separate signal generators, also referred to hereininterchangeably as signal devices, included in a vehicle can generateseparate targeted signals which are directed to separate target elementsin the environment, where the separate targeted signals include separateinstances of information which are included in the separate signalsbased on the separate target elements to which the separate targetedsignals are directed.

In the illustrated embodiment shown in FIG. 7, a vehicle 710 navigatingthrough environment 700 includes an ANS 712 and separate sets 713A-B ofsignal generators. The vehicle 710 is being navigated along lane 752 ofroadway 750. The environment 700 further includes dynamic elements 720,730, where element 720 includes a vehicle navigating along lane 754 ofroadway 750 and element 730 includes a pedestrian navigating alongsidewalk 760 which extends along an edge of the roadway 750 which isproximate to lane 752.

As shown in the illustrated embodiment, vehicle 710 generates separatetargeted signals 750A-B which are separately directed to a separate oneof elements 720, 730 in environment 700.

Targeted signal 750A is generated by a particular set of signalgenerators 713A included in vehicle 710 and is directed towards vehicle720 along a particular axis 752A and angle 751A of transmission, suchthat signal 750A passes through a limited portion of environment 700 inwhich vehicle 720 passes, so that the signal 750A is received by alimited portion of the elements 720, 730 included in the environment700. ANS 712 can determine a particular axis 752A and angle 751A of atargeted signal to direct to element 720 and can select a particularconfiguration of signal generators 713A which can generate and transmitthe signal 750A along the particular axis 752A and angle 751A. ANS 712can further command the selected signal generators 713A to generate thetargeted signal 750A including a particular set of information, alsoreferred to herein as a particular set of content, and directed, alongaxis 752A and angle 751A, towards element 720.

ANS 712 can determine the axis 752A and angle 751A of the signal 750Abased on identification of a size, position, velocity, acceleration,etc. of the dynamic element 720 through the environment, a predictedtrajectory of the element 720 through the environment, some combinationthereof, etc. The signal 750A can include information which includes amessage which, when communicates one or more signals, alerts, messages,etc. to element 720. For example, in some embodiments, signal 750A caninclude a message which communicates, to element 720, informationregarding traffic conditions, particular dynamic elements, events, etc.associated with one or more portions of environment 700. Signal 750A caninclude information indicating an occurrence of stopped vehicles in aportion of the environment 700 which through which vehicle 710 haspreviously navigated. Signal 750A can include information whichcommunicates, to vehicle 720, a driving route along which vehicle 710 isbeing navigated by ANS 712. Signal 750A can include a warning signal.

ANS 712 can determine to generate signal 750A, determine a particularangle 751A and axis 752A of signal 750A, select a particular set ofsignal generators 713A to generate the signal 750A in a particulargenerator configuration, determine one or more particular instances ofinformation to include in the signal, command the set of generators 713Ato generate the targeted signal, some combination thereof, etc. based atleast in part upon one or more of detecting the dynamic element 720 inthe environment, generating a predicted trajectory of the dynamicelement 720 through the environment 700, some combination thereof, etc.

Targeted signal 750B is generated by a particular set of signalgenerators 713B included in vehicle 710 and is directed towardspedestrian 730 along a particular axis 752B and angle 751B oftransmission, such that signal 750B passes through a limited portion ofenvironment 700 in which pedestrian 730 passes, so that the signal 750Bis received by a limited portion of the elements 720, 730 included inthe environment 700. ANS 712 can determine a particular axis 752B andangle 751B of a targeted signal 750B to direct to element 730 and canselect a particular configuration of signal generators 713B which cangenerate and transmit the signal 750B along the particular axis 752B andangle 751B. ANS 712 can further command the selected signal generators713B to generate the targeted signal 750B including a particular set ofinformation and directed, along axis 752B and angle 751B, towardselement 730. ANS 712 can determine the axis 752B and angle 751B of thesignal 750B based on identification of a size, position, velocity,acceleration, etc. of the dynamic element 730 through the environment, apredicted trajectory of the element 730 through the environment, somecombination thereof, etc. The signal 750B can include information whichincludes a message which, when received at dynamic element 730,communicates one or more signals, alerts, messages, etc. to element 730.For example, in some embodiments, signal 750B can include a messagewhich communicates, to element 730, information regarding trafficconditions, particular dynamic elements, events, etc. associated withone or more portions of environment 700. Signal 750B can includeinformation which communicates, to pedestrian 730, a driving route alongwhich vehicle 710 is being navigated by ANS 712. Signal 750B can includea warning signal.

ANS 712 can determine to generate signal 750B, determine a particularangle 751B and axis 752B of signal 750B, select a particular set ofsignal generators 713B to generate the signal 750B in a particulargenerator configuration, determine one or more particular instances ofinformation to include in the signal, command the set of generators 713Bto generate the targeted signal, some combination thereof, etc. based atleast in part upon one or more of detecting the dynamic element 730 inthe environment, generating a predicted trajectory of the dynamicelement 730 through the environment 700, some combination thereof, etc.For example, as shown, ANS 712 can determine that, where dynamic element730 is a pedestrian, a field of view 734 of the pedestrian 730 and oneor more predicted trajectories 732-B through the environment 700. Basedat least in part upon one or more of determining that the vehicle 710 isnot within the field of view 734 of the pedestrian 730, determining thatone or more predicted trajectories 732A-B of the pedestrian mayintersect a driving route along which the vehicle 710 is beingnavigated, some combination thereof, etc.

ANS 712 can determine a targeted signal to transmit to pedestrian 730which includes information which communicates one or more of a warningto the pedestrian 730 of the presence of the vehicle 710 in theenvironment 700, a message to the pedestrian 730 to refrain fromnavigating along one or more particular trajectories 732A-B through theenvironment, etc. For example, the signal 750B can include an audiomessage which warns the pedestrian 730 to avoid moving into the lane 752of the roadway 750. As a result, the vehicle 710 can respond to aprediction, at ANS 712, that the pedestrian 730 may move along atrajectory which intersects a driving route of the vehicle 710 by,rather than adjusting the driving route of the vehicle 710 to avoidintersection with the predicted trajectory of the pedestrian, generate atargeted signal which prompts the pedestrian to avoid moving along atrajectory which intersects the present driving route. As a result, therisk of paths intersecting between the vehicle 710 and dynamic elementsin the external environment through which the vehicle 710 is beingnavigated can be reduced, thereby augmenting safety for occupants ofvehicle 710 and various dynamic elements in the environment 700.

In some embodiments, one or more of the targeted signals 750A-B includesa visual signal. For example, the targeted signal 750A can be generatedby one or more visual signal generators 713A, including one or morelights, included in the vehicle 710, where a particular set of visualindicators are activated to generate a particular visual signal 750Awhich includes one or more instances of information. The visualindicators 713A can include at least a portion of one or more headlightassemblies included in the vehicle 710, where a portion of the headlightassemblies can be adjusted to direct a light beam having a particularaxis 752A and angle 751A to a particular dynamic element 720 in theenvironment 700. The headlight assemblies can be adjusted to provide avisual signal 750A which includes a variable-intensity beam of light,including a series of light beam pulses, etc.

In some embodiments, one or more of the targeted signals 750A-B includesan audio signal which is directed at a particular dynamic element,including a traffic participant, instance of fauna, etc. located in theexternal environment. For example, the targeted signal 750B can includean audio signal which can be a directional signal which is focused inangle and axis via various known systems and methods of focused audiosignals, including one or more of beamforming, ultrasonic modulation,etc., so that the recipient of the audio signal 750B is at leastpartially restricted to the particular dynamic element 730 to which thetargeted signal 750B is directed. As a result, the amplitude of thesignal can be reduced, relative to a non-focused audio signal, which canresult in reduced disturbance in the external environment as a result ofthe signal transmission. In addition, as a result of the amplitude ofthe signal being reduced, information communicated to the dynamicelement via the targeted signal can be at least partially precluded frombeing received and interpreted by other dynamic elements in theenvironment, thereby providing at least some information security.

In some embodiments, ANS 712 selects a type of targeted signal togenerate and direct to a particular dynamic element based on one or morevarious identified contextual cues associated with the particulardynamic element, a position, velocity, acceleration, etc. of one or moreof the particular dynamic element and the vehicle 710 through theenvironment 700, some combination thereof, etc. For example, ANS 712 candetermine to generate signal 750A as a visual signal based at least inpart upon a determination that dynamic element 720 is a vehicle, thatthe vehicle 710 is included within a field of view of the vehicle 720,that one or more of vehicles 710, 720 are moving through environment 700within a certain range of velocities, that a distance between vehicles710, 720 is greater than a certain threshold distance, some combinationthereof, etc. In another example, ANS 712 can determine to generatesignal 750B as an audio signal based at least in part upon adetermination that dynamic element 730 is a pedestrian, that the vehicle710 is not included within the field of view 734 of the pedestrian 730,that, that a distance between vehicle 710 and pedestrian 730 is lessthan a certain threshold distance, some combination thereof, etc.

In some embodiments, ANS 712 determines to refrain from generating atargeted signal directed to a particular target dynamic element, basedat least in part upon one or more of relative proximity, relativevelocity, etc. of the target dynamic element and the vehicle in whichthe ANS 712 is included. For example, where the relative velocity ofvehicle 710 and vehicle 720 exceeds a threshold, the value provided bysignal 750A may be restricted, as amount of elapsed time between thesignal 750A being received at vehicle 720 and vehicles 710, 720 passingeach other may be less than an estimated amount of time required for thesignal 750A to be processed at vehicle 720.

FIG. 8 illustrates generating targeted signals which are directed toparticular target dynamic elements, according to some embodiments. Thegenerating can be implemented by one or more portions of any embodimentof ANS included in any embodiments herein. An ANS can be implemented byone or more computer systems.

At 802, a dynamic element is identified in an external environment. Theidentification can be based at least in part upon processing one or moreinstances of sensor data generated by one or more sensor devicesincluded in one or more vehicles in the external environment.Identifying the dynamic element can include identifying one or morecontextual cues associated with the dynamic element, generating one ormore predicted trajectories of the dynamic element through theenvironment, etc.

At 804, a determination is made regarding whether to generate a targetedsignal which is directed to the identified dynamic element. Thedetermination can be based at least in part upon one or more of adetermination of whether the vehicle in which the ANS implementingdetermination 804 is included is located within a field of view of thedynamic element, a determination of whether a predicted trajectory ofthe dynamic element intersects a driving route along which the vehiclein which the ANS implementing determination 804 is included is locatedis being navigated, etc., a determination regarding whether the dynamicelement is moving along a trajectory which approaches one or moreelements in the external environment previously detected based onprocessing sensor data, etc.

In some embodiments, a determination regarding whether to generate atargeted signal is based at least in part upon a determination regardingwhether a present velocity of the vehicle in which the ANS implementingdetermination 804 is included is greater than a threshold value. Forexample, if the vehicle is moving greater than a threshold velocity, adetermination can be made to not generate a targeted signal, as the highvelocity of the vehicle can at least partially preclude generatedsignals from being properly received and interpreted by a target dynamicelement prior to the vehicle passing a closest proximity to the targetdynamic element.

At 806, if a determination is made to generate a targeted signal whichis directed to the dynamic element, a signal type of the signal, and oneor more instances of content to be included in the signal, aredetermined. Various signal types can include audio signals, visualsignals, some combination thereof, etc. A signal type of the targetedsignal can be based at least in part upon one or more various contextualcues associated with the identified dynamic element, etc. For example,where a contextual cue associated with a dynamic element indicates thatthe dynamic element is a pedestrian, the signal type determined at 806can include an audio signal type. In another example, where a contextualcue associated with the dynamic element indicates that the dynamicelement is a vehicle, the signal type determined at 806 can include avisual signal type.

The content of a signal, also referred to herein interchangeably as oneor more instances of information included in the signal, can bedetermined based on one or more of the field of view of the dynamicelement, a predicted trajectory of the dynamic element, one or moreelements of the external environment, etc. For example, where the fieldof view of the dynamic element excludes the vehicle in which the ANSimplementing determination 806 is included, the signal contentdetermined at 806 can include a signal, message, alert, etc. which isconfigured to communicate a presence of the vehicle. In another example,where a predicted trajectory of the dynamic element intersects thedriving route along which the vehicle in which the ANS implementingdetermination 806 is included is being navigated, the signal contentdetermined at 806 can include a warning message which is configured towarn the dynamic element to avoid navigating along the predictedtrajectory. In another example, where the vehicle in which the ANSimplementing determination 806 is included has previously navigatedproximate to one or more particular elements in the environment,including one or more traffic accidence, construction zones, stoppedvehicles proximate to the roadway, traffic hazards, etc., the signalcontent determined at 806 can include a message which communicates oneor more instances of information regarding the one or more particularelements in the environment.

At 808, one or more of an axis and angle of the targeted signal isdetermined, which results in a determination of a configuration of thetargeted signal which results in the targeted signal, when transmittedalong the one or more determined axis and angle, passes through alimited portion of the environment in which the dynamic element islocated, so that the targeted signal is restricted from being directedto one or more other elements in the environment. At 810, an amplitudeof one or more portions of the signal is determined, which can be basedin part upon one or more of relative distance, velocity, accelerationbetween the vehicle in which the ANS implementing 810 is located and thedynamic element, a content of the signal, a dynamic element typeassociated with the dynamic element, etc.

At 812, one or more sets of signal devices, included in the vehicle,which are configurable to generate the targeted signal which includesthe determined content, amplitude, and the determined one or more of theangle and axis are selected. Selecting one or more sets of signaldevices can include determining one or more particular configurations ofthe signal devices, including orientation, adjustable position, etc.which results in the signal devices being at least partially configuredto generate the targeted signal which includes the determined content,amplitude, and the determined one or more of the angle and axis. A setof signal devices can be selected based at least in part upon adetermination that the set of signal devices comprises a minimumquantity of signal devices which can generate the targeted signal whichincludes the determined content, amplitude, and the determined one ormore of the angle and axis, etc. At 814, the selected signal devices arecommanded to generate targeted signal, where the commanding can includecommanding the one or more selected signal devices to be adjustablypositioned, oriented, etc. to generate a signal which include thedetermined one or more of the determined angle and axis of the targetedsignal.

FIG. 9 illustrates an example computer system 900 that may be configuredto include or execute any or all of the embodiments described above. Indifferent embodiments, computer system 900 may be any of various typesof devices, including, but not limited to, a personal computer system,desktop computer, laptop, notebook, tablet, slate, pad, or netbookcomputer, cell phone, smartphone, PDA, portable media device, mainframecomputer system, handheld computer, workstation, network computer, acamera or video camera, a set top box, a mobile device, a consumerdevice, video game console, handheld video game device, applicationserver, storage device, a television, a video recording device, aperipheral device such as a switch, modem, router, or in general anytype of computing or electronic device.

Various embodiments of an autonomous navigation system (ANS), asdescribed herein, may be executed in one or more computer systems 900,which may interact with various other devices. Note that any component,action, or functionality described above with respect to FIGS. 1 through8 may be implemented on one or more computers configured as computersystem 900 of FIG. 9, according to various embodiments. In theillustrated embodiment, computer system 900 includes one or moreprocessors 910 coupled to a system memory 920 via an input/output (I/O)interface 930. Computer system 900 further includes a network interface940 coupled to I/O interface 930, and one or more input/output devices,which can include one or more user interface (also referred to as “inputinterface”) devices. In some cases, it is contemplated that embodimentsmay be implemented using a single instance of computer system 900, whilein other embodiments multiple such systems, or multiple nodes making upcomputer system 900, may be configured to host different portions orinstances of embodiments. For example, in one embodiment some elementsmay be implemented via one or more nodes of computer system 900 that aredistinct from those nodes implementing other elements.

In various embodiments, computer system 900 may be a uniprocessor systemincluding one processor 910, or a multiprocessor system includingseveral processors 910 (e.g., two, four, eight, or another suitablenumber). Processors 910 may be any suitable processor capable ofexecuting instructions. For example, in various embodiments processors910 may be general-purpose or embedded processors implementing any of avariety of instruction set architectures (ISAs), such as the x86,PowerPC, SPARC, or MIPS ISAs, or any other suitable ISA. Inmultiprocessor systems, each of processors 910 may commonly, but notnecessarily, implement the same ISA.

System memory 920 may be configured to store program instructions, data,etc. accessible by processor 910. In various embodiments, system memory920 may be implemented using any suitable memory technology, such asstatic random access memory (SRAM), synchronous dynamic RAM (SDRAM),nonvolatile/Flash-type memory, or any other type of memory. In theillustrated embodiment, program instructions included in memory 920 maybe configured to implement some or all of an ANS, incorporating any ofthe functionality described above. Additionally, existing automotivecomponent control data of memory 920 may include any of the informationor data structures described above. In some embodiments, programinstructions and/or data may be received, sent or stored upon differenttypes of computer-accessible media or on similar media separate fromsystem memory 920 or computer system 900. While computer system 900 isdescribed as implementing the functionality of functional blocks ofprevious Figures, any of the functionality described herein may beimplemented via such a computer system.

In one embodiment, I/O interface 930 may be configured to coordinate I/Otraffic between processor 910, system memory 920, and any peripheraldevices in the device, including network interface 940 or otherperipheral interfaces, such as input/output devices 950. In someembodiments, I/O interface 930 may perform any necessary protocol,timing or other data transformations to convert data signals from onecomponent (e.g., system memory 920) into a format suitable for use byanother component (e.g., processor 910). In some embodiments, I/Ointerface 930 may include support for devices attached through varioustypes of peripheral buses, such as a variant of the Peripheral ComponentInterconnect (PCI) bus standard or the Universal Serial Bus (USB)standard, for example. In some embodiments, the function of I/Ointerface 930 may be split into two or more separate components, such asa north bridge and a south bridge, for example. Also, in someembodiments some or all of the functionality of I/O interface 930, suchas an interface to system memory 920, may be incorporated directly intoprocessor 910.

Network interface 940 may be configured to allow data to be exchangedbetween computer system 900 and other devices attached to a network 985(e.g., carrier or agent devices) or between nodes of computer system900. Network 985 may in various embodiments include one or more networksincluding but not limited to Local Area Networks (LANs) (e.g., anEthernet or corporate network), Wide Area Networks (WANs) (e.g., theInternet), wireless data networks, some other electronic data network,or some combination thereof. In various embodiments, network interface940 may support communication via wired or wireless general datanetworks, such as any suitable type of Ethernet network, for example;via telecommunications/telephony networks such as analog voice networksor digital fiber communications networks; via storage area networks suchas Fibre Channel SANs, or via any other suitable type of network and/orprotocol.

Input/output devices may, in some embodiments, include one or moredisplay terminals, keyboards, keypads, touchpads, scanning devices,voice or optical recognition devices, or any other devices suitable forentering or accessing data by one or more computer systems 900. Multipleinput/output devices may be present in computer system 900 or may bedistributed on various nodes of computer system 900. In someembodiments, similar input/output devices may be separate from computersystem 900 and may interact with one or more nodes of computer system900 through a wired or wireless connection, such as over networkinterface 940.

Memory 920 may include program instructions, which may beprocessor-executable to implement any element or action described above.In one embodiment, the program instructions may implement the methodsdescribed above. In other embodiments, different elements and data maybe included. Note that data may include any data or informationdescribed above.

Those skilled in the art will appreciate that computer system 900 ismerely illustrative and is not intended to limit the scope ofembodiments. In particular, the computer system and devices may includeany combination of hardware or software that can perform the indicatedfunctions, including computers, network devices, Internet appliances,PDAs, wireless phones, pagers, etc. Computer system 900 may also beconnected to other devices that are not illustrated, or instead mayoperate as a stand-alone system. In addition, the functionality providedby the illustrated components may in some embodiments be combined infewer components or distributed in additional components. Similarly, insome embodiments, the functionality of some of the illustratedcomponents may not be provided and/or other additional functionality maybe available.

Those skilled in the art will also appreciate that, while various itemsare illustrated as being stored in memory or on storage while beingused, these items or portions of them may be transferred between memoryand other storage devices for purposes of memory management and dataintegrity. Alternatively, in other embodiments some or all of thesoftware components may execute in memory on another device andcommunicate with the illustrated computer system via inter-computercommunication. Some or all of the system components or data structuresmay also be stored (e.g., as instructions or structured data) on acomputer-accessible medium or a portable article to be read by anappropriate drive, various examples of which are described above. Insome embodiments, instructions stored on a computer-accessible mediumseparate from computer system 900 may be transmitted to computer system900 via transmission media or signals such as electrical,electromagnetic, or digital signals, conveyed via a communication mediumsuch as a network and/or a wireless link. Various embodiments mayfurther include receiving, sending or storing instructions and/or dataimplemented in accordance with the foregoing description upon acomputer-accessible medium. Generally speaking, a computer-accessiblemedium may include a non-transitory, computer-readable storage medium ormemory medium such as magnetic or optical media, e.g., disk orDVD/CD-ROM, volatile or non-volatile media such as RAM (e.g. SDRAM, DDR,RDRAM, SRAM, etc.), ROM, etc. In some embodiments, a computer-accessiblemedium may include transmission media or signals such as electrical,electromagnetic, or digital signals, conveyed via a communication mediumsuch as network and/or a wireless link.

The methods described herein may be implemented in software, hardware,or a combination thereof, in different embodiments. In addition, theorder of the blocks of the methods may be changed, and various elementsmay be added, reordered, combined, omitted, modified, etc. Variousmodifications and changes may be made as would be obvious to a personskilled in the art having the benefit of this disclosure. The variousembodiments described herein are meant to be illustrative and notlimiting. Many variations, modifications, additions, and improvementsare possible. Accordingly, plural instances may be provided forcomponents described herein as a single instance. Boundaries betweenvarious components, operations and data stores are somewhat arbitrary,and particular operations are illustrated in the context of specificillustrative configurations. Other allocations of functionality areenvisioned and may fall within the scope of claims that follow. Finally,structures and functionality presented as discrete components in theexample configurations may be implemented as a combined structure orcomponent. These and other variations, modifications, additions, andimprovements may fall within the scope of embodiments as defined in theclaims that follow.

What is claimed is:
 1. An apparatus, comprising: an autonomousnavigation system configured to be installed in a vehicle andautonomously navigate the vehicle through an environment in which thevehicle is located, wherein the autonomous navigation system isconfigured to: identify a set of contextual cues associated with adynamic element located in the environment, wherein each contextual cueindicates one or more particular features associated with the dynamicelement, based on monitoring at least a portion of the environment;associate the dynamic element with a particular set of predictedmotions, based on a determination of a correlation between theidentified set of contextual cues and a predetermined set of contextualcues which are associated with the particular set of predicted motions;generate a predicted trajectory of the dynamic element through theenvironment based on the particular set of predicted motions associatedwith the dynamic element; and generate a set of control commands which,when executed by one or more control elements installed in the vehicle,cause the vehicle to be navigated along a driving route that accountsfor the predicted trajectory of the dynamic element.
 2. The apparatus ofclaim 1, wherein the autonomous navigation system is configured to:prior to identifying the set of contextual cues associated with thedynamic element located in the environment: identify a set of contextualcues associated with another dynamic element located in the environment,wherein each contextual cue indicates one or more particular featuresassociated with the other dynamic element, based on monitoring at leasta portion of the environment; monitor a particular set of motionsexecuted by the other dynamic element through the environment,subsequent to identifying the set of contextual cues associated with theother dynamic element; and based on the monitoring, generate anassociation of the set of contextual cues, as the set of predeterminedcontextual cues, with the particular set of motions executed by theother dynamic element, as the particular set of predicted motions;wherein the association specifies that dynamic elements associated withthe set of predetermined contextual cues are predicted to execute theparticular set of predicted motions.
 3. The apparatus of claim 2,wherein the autonomous navigation system is configured to: monitor aparticular set of actual motions executed by the dynamic element throughthe environment, subsequent to associating the dynamic element with theparticular set of predicted motions; and based on a determination thatthe particular set of actual motions executed by the dynamic element aredistinct from the particular set of predicted motions, associate thepredetermined set of contextual cues with the particular set of actualmotions and disassociating the predetermined set of contextual cues fromthe particular set of predicted motions.
 4. The apparatus of claim 1,wherein: the set of contextual cues comprises a specification of aposition and velocity of the dynamic element relative to one or moreparticular static elements detected in the environment.
 5. The apparatusof claim 1, wherein: the set of contextual cues comprises aspecification of a position and velocity of the dynamic element relativeto the one or more other dynamic elements detected in the environment.6. The apparatus of claim 1, comprising: one or more sets of signalgenerators which are configured to generate and direct one or moretargeted signals to one or more elements located in the environment; andan autonomous navigation system configured to: command at least one ofthe one or more sets of signal generators to generate a particulartargeted signal, comprising a particular instance of content selectedbased on at least one sensor data representation of the dynamic elementand a particular signal beam angle which intersects a limited portion,of the environment, in which the particular element is located, suchthat the particular instance of content is communicated to the dynamicelement in the environment to the exclusion of a remainder portion ofthe environment.
 7. The apparatus of claim 6, wherein the one or moresets of signal generators comprise one or more sets of speaker deviceswhich are configured to generate one or more targeted signals to one ormore elements located in the environment based on at least one of:beamforming; or ultrasonic modulation.
 8. A method, comprising:performing, by one or more computer systems installed in a vehiclelocated in a particular environment: identifying a set of contextualcues associated with a dynamic element located in the environment,wherein each contextual cue indicates one or more particular featuresassociated with the dynamic element, based on monitoring at least aportion of the environment; associating the dynamic element with aparticular set of predicted motions, based on a determination of acorrelation between the identified set of contextual cues and apredetermined set of contextual cues which are associated with theparticular set of predicted motions; generating a predicted trajectoryof the dynamic element through the environment based on the particularset of predicted motions associated with the dynamic element; andgenerating a set of control commands which, when executed by one or morecontrol elements installed in the vehicle, cause the vehicle to benavigated along a driving route that accounts for the predictedtrajectory of the dynamic element.
 9. The method of claim 8, comprising:prior to identifying the set of contextual cues associated with thedynamic element located in the environment: identifying a set ofcontextual cues associated with another dynamic element located in theenvironment, wherein each contextual cue indicates one or moreparticular features associated with the other dynamic element, based onmonitoring at least a portion of the environment; monitoring aparticular set of motions executed by the other dynamic element throughthe environment, subsequent to identifying the set of contextual cuesassociated with the other dynamic element; and based on the monitoring,generating an association of the set of contextual cues, as the set ofpredetermined contextual cues, with the particular set of motionsexecuted by the other dynamic element, as the particular set ofpredicted motions; wherein the association specifies that dynamicelements associated with the set of predetermined contextual cues arepredicted to execute the particular set of predicted motions.
 10. Themethod of claim 9, comprising: monitoring a particular set of actualmotions executed by the dynamic element through the environment,subsequent to associating the dynamic element with the particular set ofpredicted motions; and based on a determination that the particular setof actual motions executed by the dynamic element are distinct from theparticular set of predicted motions, associating the predetermined setof contextual cues with the particular set of actual motions anddisassociating the predetermined set of contextual cues from theparticular set of predicted motions.
 11. The method of claim 8, wherein:the set of contextual cues comprises a specification of a position andvelocity of the dynamic element relative to one or more particularstatic elements detected in the environment.
 12. The method of claim 8,wherein: the set of contextual cues comprises a specification of aposition and velocity of the dynamic element relative to the one or moreother dynamic elements detected in the environment.
 13. The method ofclaim 8, comprising: commanding at least one set of one or more signalgenerators installed in the vehicle to generate a particular targetedsignal, comprising a particular instance of content selected based on atleast one sensor data representation of the dynamic element and aparticular signal beam angle which intersects a limited portion, of theenvironment, in which the particular element is located, such that theparticular instance of content is communicated to the dynamic element inthe environment to the exclusion of a remainder portion of theenvironment.
 14. The method of claim 13, wherein the one or more sets ofsignal generators comprise one or more sets of speaker devices which areconfigured to generate one or more targeted signals to one or moreelements located in the environment based on at least one of:beamforming; or ultrasonic modulation.
 15. A non-transitory,computer-readable medium storing a program of instructions which, whenexecuted by at least one computer system, causes the at least onecomputer system to: identify a set of contextual cues associated with adynamic element located in the environment, wherein each contextual cueindicates one or more particular features associated with the dynamicelement, based on monitoring at least a portion of the environment;associate the dynamic element with a particular set of predictedmotions, based on a determination of a correlation between theidentified set of contextual cues and a predetermined set of contextualcues which are associated with the particular set of predicted motions;generate a predicted trajectory of the dynamic element through theenvironment based on the particular set of predicted motions associatedwith the dynamic element; and generate a set of control commands which,when executed by one or more control elements installed in the vehicle,cause the vehicle to be navigated along a driving route that accountsfor the predicted trajectory of the dynamic element.
 16. Thenon-transitory, computer readable medium of claim 15, wherein theprogram of instruction, when executed by the at least one computersystem, cause the at least one computer system to: prior to identifyingthe set of contextual cues associated with the dynamic element locatedin the environment: identify a set of contextual cues associated withanother dynamic element located in the environment, wherein eachcontextual cue indicates one or more particular features associated withthe other dynamic element, based on monitoring at least a portion of theenvironment; monitor a particular set of motions executed by the otherdynamic element through the environment, subsequent to identifying theset of contextual cues associated with the other dynamic element; andbased on the monitoring, generate an association of the set ofcontextual cues, as the set of predetermined contextual cues, with theparticular set of motions executed by the other dynamic element, as theparticular set of predicted motions; wherein the association specifiesthat dynamic elements associated with the set of predeterminedcontextual cues are predicted to execute the particular set of predictedmotions.
 17. The non-transitory, computer readable medium of claim 15,wherein: the set of contextual cues comprises a specification of aposition and velocity of the dynamic element relative to one or moreparticular static elements detected in the environment.
 18. Thenon-transitory, computer readable medium of claim 15, wherein: the setof contextual cues comprises a specification of a position and velocityof the dynamic element relative to the one or more other dynamicelements detected in the environment.
 19. The non-transitory, computerreadable medium of claim 15, wherein the program of instruction, whenexecuted by the at least one computer system, cause the at least onecomputer system to: command at least one set of one or more signalgenerators installed in the vehicle to generate a particular targetedsignal, comprising a particular instance of content selected based on atleast one sensor data representation of the dynamic element and aparticular signal beam angle which intersects a limited portion, of theenvironment, in which the particular element is located, such that theparticular instance of content is communicated to the dynamic element inthe environment to the exclusion of a remainder portion of theenvironment.
 20. The non-transitory, computer readable medium of claim19, wherein the one or more sets of signal generators comprise one ormore sets of speaker devices which are configured to generate one ormore targeted signals to one or more elements located in the environmentbased on at least one of: beamforming; or ultrasonic modulation.